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or TensorFlow to develop state of the art machine learning pipelines. Perform statistical analysis in languages including R and Python Work Location: Hybrid – This role is eligible for a hybrid schedule of 2
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one or more programming languages (e.g., R, Python, Perl, Java, C++) and willingness to learn new programming languages as necessary. Familiarity with statistical analytical concepts and methods
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an experimental or wet lab. Experience with data analysis on protein-protein interaction, and mass spectrometry-based proteomics. Prior experience with scientific programming and statistics using R/Python. Prior
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, Python, and/or a comparable programming language, preferably in a high-performance cluster computing environment and using version control. Experience developing and/or applying machine learning methods
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, deep learning, and statistical modeling techniques. Proficiency in programming languages such as Python, R, or C++, with experience using AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn
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database software Development programming languages (such as Java, JavaScript, Python, Salesforce Apex etc.) Relational databases in an Oracle client/server environment SQL and writing queries against
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implementation of cloud storage and data management strategies for complex research data sets Ability to work on multiple projects simultaneously Coding experience (python, Matlab, C) Experience with database
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., computational neuroscience, bioinformatics, biomedical engineering, data science, or a related discipline). At least 3 years of experience using R, Python, and/or a comparable programming language, preferably in
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any of the following: Electrophysiology Multiphoton or confocal imaging Histology, CLARITY, in-situ hybridization Programming (Matlab/IgorPro/Python), electronics fabrication How to Apply: For full
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molecule/drug applications. Bioinformatics and/or programming expertise in languages such as R and Python. Knowledge, Skills and Abilities: Solid understanding of common cellular and molecular mechanisms